Takayasu’s arteritis is an idiopathic inflammatory disease involving the main vessels. Acute stroke as the initial presentation in patients with Takayasu’s arteritis is rarely reported. Herein, we report the case of a 36-year-old woman who complained of acute weakness in the left limbs. The lack of a pulse in the distal artery and the difference in blood pressure between limbs were observed in the emergency department. Takayasu’s arteritis complicated with acute ischemic stroke was diagnosed based on the angiographs. The relevant literature is also reviewed.
Takayasu Arteritis

Nerve root compression due to ligamentum flavum hematoma is extremely rare, with less than 70 cases reported in the literature. The clinical presentation and images were similar to those of spinal epidural tumors. Herein, we reported a previously healthy 64-year-old female who presented with right radicular leg pain. Neurological examination was consistent with right L5 root compression. The magnetic resonance imaging revealed a mass posterior to the L5 thecal sac, appearing as high intensity on T1-weighted and T2-weighted images. During operation, the dark hematoma within the ligamentum flavum was found. The pathological examination confirmed the diagnosis of hemorrhage. Her prognosis following surgery was excellent.
Sciatica

Cervical spinal manipulation is considered to be a safe procedure for treating patients with neck pain and muscle-tension headache. Rarely has acute cervical spinal epidural hematoma after spinal manipulation been reported. Here, we report a 16-year-old healthy male adolescent who presented with progressive weakness in the right extremities following acute neck and shoulder pain after spinal manipulation from Acute cervical spinal epidural hematoma with compression of spinal cord. After emergency surgery the patient had full recovery from the profound neurological deficits.
Hematoma, Epidural, Spinal

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.